Universität Wien
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260096 VU Quantum Information Theory -Quantum Computing & Machine Learning (2024W)

5.00 ECTS (3.00 SWS), SPL 26 - Physik
Prüfungsimmanente Lehrveranstaltung
Moodle

An/Abmeldung

Hinweis: Ihr Anmeldezeitpunkt innerhalb der Frist hat keine Auswirkungen auf die Platzvergabe (kein "first come, first served").

Details

max. 15 Teilnehmer*innen
Sprache: Englisch

Lehrende

Termine (iCal) - nächster Termin ist mit N markiert

  • Montag 07.10. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 14.10. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 21.10. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 28.10. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 04.11. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 11.11. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 18.11. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 25.11. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 02.12. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 09.12. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 16.12. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 13.01. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien
  • Montag 20.01. 08:30 - 11:00 Erwin-Schrödinger-Hörsaal, Boltzmanngasse 5, 5. Stk., 1090 Wien

Information

Ziele, Inhalte und Methode der Lehrveranstaltung

[This course is planned as a face-to-face course and attendance is mandatory.]

This course gives an introduction to quantum information theory with a focus on quantum computing and machine learning with quanta, mainly from a theoretical point of view, but experimental possibilities will also be discussed. The course will also provide practical exercises, e.g. a set of quantum gates will be provided with which we can build and test basic quantum algorithms. The implementation on current and future quantum computers will be discussed.

The course builds on the knowledge of a basic course on quantum mechanics and introduces qubits, quantum gates, circuits, measurement problems, quantum algorithms, artificial neural networks, simple machine learning algorithms (e.g. PCA, k-means), error correction methods and basics of decoherence. (Classical) machine learning is not required, an introduction will be given before the quantum versions are discussed.

Method: Lectures, in-class problem solving, hands-on and take-home problems.

The course will be held either in English or German, depending on student preference.

Art der Leistungskontrolle und erlaubte Hilfsmittel

This event is an interactive one, therefore the final grade is an average of active and regular participation, short exams within the event (announced in due time) and home-works/reports. No absence without announcement beforehand (per email).

Mindestanforderungen und Beurteilungsmaßstab

basics in quantum mechanics; average between regular (mandatory) attendance*, activity (25%), short exams (25%) and home-works/reports (50%).
*No-one who is ill or feels ill is allowed to attend the course. These absences must be announced by e-mail before the course and can be compensated by written work.

Prüfungsstoff

everything discussed in the lectures

Literatur

will be given in the lectures

Zuordnung im Vorlesungsverzeichnis

M-VAF A 2, M-VAF B

Letzte Änderung: Fr 04.10.2024 12:06